Should early cranial MRI of preterm infants become routine?

Development and validation of a diagnostic prediction model for severe periventricular-intraventricular hemorrhage in newborns: insights from a retrospective analysis utilizing the MIMIC-III database

OBJECTIVE

Periventricular-intraventricular hemorrhage is the most common type of intracranial bleeding in newborns, especially in the first 3 days after birth. Severe periventricular-intraventricular hemorrhage is considered a progression from mild periventricular-intraventricular hemorrhage and is often closely associated with severe neurological sequelae. However, no specific indicators are available to predict the progression from mild to severe periventricular-intraventricular in early admission. This study aims to establish an early diagnostic prediction model for severe PIVH.

METHOD

This study was a retrospective cohort study with data collected from the MIMIC-III (v1.4) database. Laboratory and clinical data collected within the first 24 h of NICU admission have been used as variables for both univariate and multivariate logistic regression analyses to construct a nomogram-based early prediction model for severe periventricular-intraventricular hemorrhage and subsequently validated.

RESULTS

A predictive model was established and represented by a nomogram, it comprised three variables: output, lowest platelet count and use of vasoactive drugs within 24 h of NICU admission. The model's predictive performance showed by the calculated area under the curve was 0.792, indicating good discriminatory power. The calibration plot demonstrated good calibration between observed and predicted outcomes, and the Hosmer-Lemeshow test showed high consistency (p = 0.990). Internal validation showed the calculated area under a curve of 0.788.

CONCLUSIONS

This severe PIVH predictive model, established by three easily obtainable indicators within the NICU, demonstrated good predictive ability. It offered a more user-friendly and convenient option for neonatologists.

Precision Medicine in Neonates: A Tailored Approach to Neonatal Brain Injury

Despite advances in neonatal care to prevent neonatal brain injury and neurodevelopmental impairment, predicting long-term outcome in neonates at risk for brain injury remains difficult. Early prognosis is currently based on cranial ultrasound (CUS), MRI, EEG, NIRS, and/or general movements assessed at specific ages, and predicting outcome in an individual (precision medicine) is not yet possible. New algorithms based on large databases and machine learning applied to clinical, neuromonitoring, and neuroimaging data and genetic analysis and assays measuring multiple biomarkers (omics) can fulfill the needs of modern neonatology. A synergy of all these techniques and the use of automatic quantitative analysis might give clinicians the possibility to provide patient-targeted decision-making for individualized diagnosis, therapy, and outcome prediction. This review will first focus on common neonatal neurological diseases, associated risk factors, and most common treatments. After that, we will discuss how precision medicine and machine learning (ML) approaches could change the future of prediction and prognosis in this field.

Neuropredictors of oromotor feeding impairment in 12month-old children

BACKGROUND

Feeding impairment is prevalent in children with neurodevelopmental issues. Neuroimaging and neurobehavioral outcomes at term are predictive of later neuromotor impairment, but it is unknown whether they predict feeding impairment.

AIMS

To determine whether neurobehavior and brain magnetic resonance imaging (MRI) at term predict oromotor feeding at 12 months in preterm and term-born children.

STUDY DESIGN

Prospective cohort study.

SUBJECTS

248 infants (97 born <30 weeks and 151 born at term) recruited at birth.

OUTCOME MEASURES

Neurobehavioral assessments (General Movements (GMA), Hammersmith Neonatal Neurological Examination (HNNE), Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS)); and brain MRI were administered at term-equivalent age. Oromotor feeding was assessed at 12 months corrected age using the Schedule for Oral Motor Assessment.

RESULTS

49/227 children had oromotor feeding impairment. Neurobehavior associated with later feeding impairment was: suboptimal NNNS stress (odds ratio [OR] 2.68; 95% confidence interval [CI] 1.20–6.01), non-optimal reflexes (OR 3.33; 95% CI 1.37–8.11) and arousal scales (OR 2.54; 95% CI 1.03–6.27); suboptimal HNNE total (OR 4.69; 95% CI 2.20–10.00), reflexes (OR 2.62; 95% CI 1.06–6.49), and tone scores (OR 3.87; 95% CI 1.45–10.35); and abnormal GMA (OR 2.60; 95% CI 1.21–5.57). Smaller biparietal diameter also predicted feeding impairment (OR 0.88; 95% CI 0.79–0.97). There was little evidence that relationships differed between birth groups.

CONCLUSIONS

Neurobehavior and biparietal diameter at term are associated with oromotor feeding at 12 months. These results may identify children at greatest risk of oromotor feeding impairment.

Comparison of preterm and term equivalent age MRI for the evaluation of preterm brain injury

OBJECTIVE

To compare information obtained from preterm magnetic resonance imaging (MRI; 31-34 weeks) brain scan to that done at term equivalent age.

STUDY DESIGN

Prospective observational study of premature infants with evidence or suspicion of parenchymal brain injury on cranial ultrasound. Brain injury on two scans scored using a scoring system and analyzed.

RESULTS

Fourteen infants with a median (range) gestation at birth of 28 (25-29) weeks and birth weight of 1254 (680-1557) grams were studied. There was a strong correlation between the brain injury scores for the two scans (Spearman ρ=0.87, P=0.001) with excellent agreement between two radiologists (interclass correlation coefficient 0.9-0.94). There was also a high level of agreement between the preterm and term MRI two scores (Intraclass correlation coefficient, 0.79 (0.53-0.94)).

CONCLUSIONS

Preterm MRI is a feasible option for the assessment of preterm brain injury and analysis of data obtained from scan at preterm age is comparable to that obtained at term equivalent age.

Longitudinal change in white matter in preterm infants without magnetic resonance imaging abnormalities: Assessment of serial diffusion tensor imaging and their relationship to neurodevelopmental outcomes

PURPOSE

We used diffusion tensor imaging (DTI) to evaluate longitudinal changes in fractional anisotropy (FA) of white matter tracts in preterm infants without abnormal magnetic resonance imaging (MRI) findings. Imaging was conducted at term equivalent age (TEA) and 1year of corrected age. Furthermore, we assessed correlations between FA and neurodevelopmental outcomes at 3years of corrected age to investigate brain prematurity of preterm infants without MRI abnormalities.

METHODS

Preterm infants underwent serial MRI at TEA and 1year of corrected age. Of these, 13 infants entered a retrospective study, undergoing neurodevelopmental assessment at 3years of corrected age. These infants were divided into two groups depending on gestational age (GA): <26weeks and ⩾26weeks. DTI-based tractography was performed to obtain the FA of the motor tract, sensory tract, superior cerebellar peduncle, middle cerebellar peduncle, and corpus callosum. FA was compared between two groups, and correlations between FA and neurodevelopmental outcomes were assessed.

RESULTS

FA of the splenium at TEA was significantly different between the two groups divided according to GA. However, this difference was no longer observed at 1year of corrected age. There was no correlation between FA of the splenium at TEA and neurodevelopmental assessment scores at 3years of corrected age.

CONCLUSIONS

At TEA, FA of the splenium was lower in younger GA infants without MRI abnormalities, but this may not affect subsequent neurodevelopmental outcomes.

Changes in brain magnetic resonance imaging patterns for preterm infants after introduction of a magnetic resonance-compatible incubator coil system: 5-year experience at a single institution

OBJECTIVE

To evaluate the changes in using patterns of brain magnetic resonance imaging (MRI) in preterm infants after introduction of a MR-compatible incubator coil system.

MATERIALS AND METHODS

Brain MRIs for preterm infants with the MR-compatible incubator coil from March 2010 to July 2014 (n=154, group A) were compared with MRIs prior to the introduction of the incubator coil, from March 2005 to February 2010 (n=65, group B). Clinical data, MRI findings, acquisition time, and incidence of adverse events during the study were retrospectively reviewed. For the qualitative analysis of the examinations, the presence of motion artefact, spatial resolution, and overall image quality were assessed. Signal uniformity of each sequence was evaluated for a quantitative comparison.

RESULTS

Comparing with group B, Group A was significantly younger (36+3 vs. 38+3 weeks, p<0.001), had a significantly lower body weight (2006.6 and 2390.3g respectively; p<0.001) at the time of MRI, and had shorter time interval (54.3±2.6 vs. 70.5±4.4days, p=0.002) between birth and examination. Abnormal findings were noted more frequently in group A (n=100, 65%) than in B (n=24, 37%. p=0.001) with a significantly higher incidence of diffusion restriction (n=21, 13.6% vs. n=4, 6.2%, p=0.034). Mean image acquisition time was significantly shorter in group A (21.4±4.5 vs. 25.4±5.5min, p<0.001) with significant lower adverse events during MRI (n=26, 40 vs. n=6, 3.9%, p<0.001). Group A exhibited significantly less motion artefact, better spatial resolution, and better overall image quality with decreased signal variation than group B (all p<0.001).

CONCLUSION

Application of the MR-compatible incubator for preterm brain MRI evaluation is safer and provides more timely evaluation of preterm infants with better image quality.